This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread...

We investigate the informational content of credit default swap (CDS) spreads for future volatility of (firm) assets and equity. In the cross-section, CDS spreads are significantly more informative about future asset than equity volatility. The informational content of historical and option...

This paper investigates whether the debt quality matters and the role of debt maturity choice. At corporate level, the mismatch between the debt maturity and other performance drivers widespread unexpected risks. Shortening the maturity incentivise more liquid investments, usually the less...

Two basic solutions have been proposed to fix the well-documented incompatibility of the sample covariance matrix with Markowitz mean-variance portfolio optimization: first, restrict leverage so much that no short sales are allowed; or, second, linearly shrink the sample covariance matrix towards...

We investigate the effects of constraining leverage and shrinking covariance matrix in constructing large portfolios, both theoretically and empirically. Considering a wide variety of setups that involve conditioning or not conditioning the covariance matrix estimator on the recent past...

We investigate the effects of constraining leverage and shrinking covariance matrix in constructing large portfolios, both theoretically and empirically. Considering a wide variety of setups that involve conditioning or not conditioning the covariance matrix estimator on the recent past...

This article is devoted to the exploration of the mechanism of making decision about the company's financing structure. It is shown that the interaction between various financial characteristics of company plays statistically significant role in the capital structure determination. Namely their...

Yes, they can! Machine learning models that exploit big data identify leverage determinants and predict leverage better than classical methods. By allowing for nonlinearities and complex interactions, machine learning boosts the out-of-sample R-squared from 36% to 56% over linear methods such as...

Stock return volatility significantly predicts active leverage adjustment, consistent with the trade-off theory. Firms respond asymmetrically to rising volatility instead of falling volatility, more with debt reduction than equity issuance. The forecasting power of stock return volatility mostly...